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bladezhang

Ddzaishot

by bladezhang · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install ddzaishot
Description
提供斗地主牌局识别、自动记牌和AI出牌建议,支持屏幕扫描和辅助操作功能。
README (SKILL.md)

SKILL.md - ddzaishot 斗地主AI助手

当你需要帮助用户玩斗地主或分析牌局时,使用此技能。

功能

  • 🎯 识别屏幕上的牌
  • 📝 自动记牌
  • 🧠 AI推荐出牌
  • 🖱️ 辅助出牌(可选)

调用方式

扫描屏幕识别牌局

cd ddzaishot
python src/api.py scan

AI推荐出牌(需先设置牌)

# 设置我的牌和地主
python src/api.py suggest --cards=3,4,5,6,7,8,9,10,11,12,13,14,15 --landlord=me

# 演示模式(随机发牌测试)
python src/api.py demo

查看当前状态

python src/api.py status

牌值对应

  • 3-10: 数字牌
  • 11: J
  • 12: Q
  • 13: K
  • 14: A
  • 15: 2
  • 16: 小王
  • 17: 大王

交互式模式

python src/main.py

然后输入命令:

  • s 扫描屏幕
  • p 推荐出牌
  • m 手动输入牌
  • l 设置地主
  • d 演示模式

注意事项

  1. 屏幕识别需要先制作卡牌模板放到 templates/ 目录
  2. 鼠标控制需要先运行 c 命令校准
  3. 建议先在演示模式下测试AI逻辑

依赖

pip install opencv-python numpy pyautogui pillow mss keyboard
Usage Guidance
This skill appears to be what it says: it captures your screen, reads card images (using templates), keeps game state, suggests plays, and can optionally control the mouse to click in the game. Before installing/using: 1) Only run it when no sensitive windows are visible—it takes and saves screenshots to logs/. 2) Prepare templates/ as described and test in demo mode first; do not enable automatic play until you verify positions via calibration. 3) The skill uses pyautogui to perform clicks; be aware auto-mode can interact with any foreground UI (pyautogui.FAILSAFE is set, but treat with caution). 4) Dependencies are standard PyPI packages—install them in a virtual environment. 5) There are no network calls or credential requests. If you want extra assurance, run the code in a sandboxed environment (or inspect templates/logs directories) before granting it interactive control of your desktop.
Capability Analysis
Type: OpenClaw Skill Name: ddzaishot Version: 1.0.0 The skill bundle implements a game assistant with high-risk capabilities, including screen capture (src/screen.py) and mouse automation (src/mouse.py) using pyautogui. It also lists the 'keyboard' library in requirements.txt and SKILL.md, which is frequently used for keylogging, although no active keylogging logic is present in the provided source files. While these features are consistent with the stated purpose of a Dou Dizhu AI, the combination of screen scraping, UI control, and unnecessary sensitive dependencies warrants a suspicious classification.
Capability Assessment
Purpose & Capability
The name/description (斗地主牌局识别、记牌、AI出牌与可选的鼠标辅助) align with the provided code: screen capture and recognition (screen.py), AI decision logic (ai.py), game state (game.py/cards.py), and mouse automation (mouse.py). Required resources (templates/, logs/) and listed Python dependencies match the feature set.
Instruction Scope
SKILL.md contains concrete, scoped commands (scan, suggest, demo, status) and instructs installing Python deps and preparing card templates. Runtime actions are limited to local screen capture, image template matching, simple OCR/heuristics, game state management, and local mouse control. The instructions do save screenshots to logs/ and require templates/ for recognition, which is documented.
Install Mechanism
No automated install spec is present; the skill is instruction/code-only. Dependencies are standard PyPI packages (opencv-python, numpy, pyautogui, pillow, mss, keyboard) listed in requirements.txt and SKILL.md. No downloads from arbitrary URLs or archive extraction are used.
Credentials
The skill requests no environment variables, no credentials, and accesses only local files/directories (templates/, logs/). There are no network endpoints or secrets required by the code.
Persistence & Privilege
always is false and the skill does not modify other skills or system-wide configs. However, it provides automated mouse control (pyautogui) and supports an AutoPlayer mode; because the platform allows autonomous invocation by default, combining autonomous invocation with automated input can have broader impact if enabled—this is expected for an auto-play assistant but worth user attention.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ddzaishot
  3. After installation, invoke the skill by name or use /ddzaishot
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of ddzaishot 斗地主AI助手. - Supports screen card recognition, automatic card counting, and AI move suggestions. - Provides optional assisted card playing feature. - Includes interactive mode and command-line usage instructions. - Covers setup notes, card value mapping, and dependency list.
Metadata
Slug ddzaishot
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Ddzaishot?

提供斗地主牌局识别、自动记牌和AI出牌建议,支持屏幕扫描和辅助操作功能。 It is an AI Agent Skill for Claude Code / OpenClaw, with 245 downloads so far.

How do I install Ddzaishot?

Run "/install ddzaishot" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ddzaishot free?

Yes, Ddzaishot is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ddzaishot support?

Ddzaishot is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ddzaishot?

It is built and maintained by bladezhang (@bladezhang); the current version is v1.0.0.

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